Browse > Article

Multi-Objective Micro-Genetic Algorithm for Multicast Routing  

Jun, Sung-Hwa (Department of Computer Engineering, KyungHee University)
Han, Chi-Geun (Department of Computer Engineering, KyungHee University)
Publication Information
IE interfaces / v.20, no.4, 2007 , pp. 504-514 More about this Journal
Abstract
The multicast routing problem lies in the composition of a multicast routing tree including a source node and multiple destinations. There is a trade-off relationship between cost and delay, and the multicast routing problem of optimizing these two conditions at the same time is a difficult problem to solve and it belongs to a multi-objective optimization problem (MOOP). A multi-objective genetic algorithm (MOGA) is efficient to solve MOOP. A micro-genetic algorithm(${\mu}GA$) is a genetic algorithm with a very small population and a reinitialization process, and it is faster than a simple genetic algorithm (SGA). We propose a multi-objective micro-genetic algorithm (MO${\mu}GA$) that combines a MOGA and a ${\mu}GA$ to find optimal solutions (Pareto optimal solutions) of multicast routing problems. Computational results of a MO${\mu}GA$ show fast convergence and give better solutions for the same amount of computation than a MOGA.
Keywords
micro-genetic algorithm; multicast routing problem; multi-objective optimization;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Esbensen, H. (1995), Computing Near-Optimal Solutions ro the Steiner Problem in a Graph Using a Genetic Algorithm, Network, 26,173-185   DOI
2 Kompella, V. P., Pasquale,J. C, and Polyzos, G. C (1993), Multicast Routing for Multimedia Communications, IEEE/ACM Trans. on Networking, 1(3),286-292   DOI   ScienceOn
3 Krishnakumar, K. (1989), Micro-Genetic Algorithms for Stationary and NonStationary Function Optimization., SPIE Proceedings: Intelligent Control and Adaptive Systems, 1196, 289-296
4 Osyczka, A. (1985), Multicriteria Optimization for Engineering Design, Design Optimization, 193-227
5 Tsai, C. F. and Tasi, C. W. (2001), A Nobel Multicast Routing Algorithm with Delay Constraint for Multimedia Application in Wide Area Network, Info-tech and Info-net, 5, 301-305
6 Ying, L. and Jianping, W. (2002), A Genetic Algorithm for the DegreeConstrained Multicasting Problem, High Speed Networks and Mitltimedia Communications 5th IEEE International Conference on, 315-319
7 Kou, L., Markowsky, G. and Berman, L. (1981), A Fast Algorithms for Steiner Tree, Acta Informatica, 15, 141-145   DOI
8 Lee, Y. G. and Han, C G. (2004), Multi Objective Genetic Algorithm for Multi-Objective Multicast Routing, Master's Thesis Kyung Hee Univ
9 Wintet, P. (1987), Steiner Problem in Network: a Survey, Networks, 17, 129-167   DOI
10 Khare, V. (2003), Performance Scaling of Multi-Objective Evolutionary Algorithms, EMO 2003,8(11), 376-390
11 Coello, C A. and Pulido, G. T. (2001), A Micro-Genetic Algorithm for Multiobjecrive Optimization., Lecture Notes in Computer Science, 1993, 126-140   DOI
12 Murata, T. and Ishibushi, H. (1995), MOGA: Multi-Ojbective Genetic Algorithms, Proc. 2nd IEEE Int. Conf on Evolutionary Computation, 289-294
13 Hyun, C.J. and Kim, Y. G. (1996), A Genetic Algorithm for Multiple Objective Sequencing Problems in Mixed Model Assembly Lines,Journal of the Korean Institute of Industrial Engineers, 22(4), 533-549
14 Wang, B. and Hou, J. C. (2000), Multicast Routing and Its QoS Extension: Problems, Algorithms, and Protocols, IEEE Networks, 14(1),22-36   DOI   ScienceOn